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<div class="title">SimpleTensor.h</div>  </div>
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<a href="_simple_tensor_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017-2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#ifndef __ARM_COMPUTE_TEST_SIMPLE_TENSOR_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#define __ARM_COMPUTE_TEST_SIMPLE_TENSOR_H__</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_utils_8h.xhtml">arm_compute/core/Utils.h</a>&quot;</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>&quot;</span></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_i_accessor_8h.xhtml">tests/IAccessor.h</a>&quot;</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tests_2_utils_8h.xhtml">tests/Utils.h</a>&quot;</span></div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="preprocessor">#include &lt;algorithm&gt;</span></div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="preprocessor">#include &lt;array&gt;</span></div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="preprocessor">#include &lt;cstddef&gt;</span></div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="preprocessor">#include &lt;cstdint&gt;</span></div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="preprocessor">#include &lt;functional&gt;</span></div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="preprocessor">#include &lt;memory&gt;</span></div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="preprocessor">#include &lt;stdexcept&gt;</span></div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#include &lt;utility&gt;</span></div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;{</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="keyword">namespace </span>test</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;{</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="keyword">class </span>RawTensor;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">   59</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1_i_accessor.xhtml">IAccessor</a></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;{</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>, <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">fixed_point_position</a> = 0);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> shape, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>,</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;                 <span class="keywordtype">int</span>              <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>         = 1,</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;                 <span class="keywordtype">int</span>              <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">fixed_point_position</a> = 0,</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;                 <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>    = <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a>(),</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;                 <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>       <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>          = <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &amp;tensor);</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &amp;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed">operator=</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> tensor);</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &amp;&amp;) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a16d7ecd97f89cf9dc40b3fc7c9abe2cd">~SimpleTensor</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b">  107</a></span>&#160;    <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b">value_type</a> = T;</div><div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">  109</a></span>&#160;    <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">Buffer</a> = std::unique_ptr&lt;value_type[]&gt;;</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;</div><div class="line"><a name="l00111"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a467ad6d14558452f498777a7823fa252">  111</a></span>&#160;    <span class="keyword">friend</span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a>;</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    T &amp;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>);</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    <span class="keyword">const</span> T &amp;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>) <span class="keyword">const</span>;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">element_size</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">size</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00168"></a><span 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};</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;};</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00233"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a1cd44d7621633f8ae04a3a16287673">  233</a></span>&#160;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor&lt;T&gt;::SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" 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name="l00277"></a><span class="lineno">  277</span>&#160;</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;    <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;}</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00282"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">  282</a></span>&#160;T &amp;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">SimpleTensor&lt;T&gt;::operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>)</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;{</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;    <span class="keywordflow">return</span> _buffer[<a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>];</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;}</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00288"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a73aecdf45b3f257e0c15757a18573ea4">  288</a></span>&#160;<span class="keyword">const</span> T &amp;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">SimpleTensor&lt;T&gt;::operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>)<span class="keyword"> const</span></div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;    <span class="keywordflow">return</span> _buffer[<a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>];</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;}</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00294"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">  294</a></span>&#160;<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">SimpleTensor&lt;T&gt;::shape</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;    <span class="keywordflow">return</span> _shape;</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;}</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">  300</a></span>&#160;<span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">SimpleTensor&lt;T&gt;::element_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>() * <a class="code" href="namespacearm__compute.xhtml#a34b06c0cd94808a77b697e79880b84b0">element_size_from_data_type</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>());</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;}</div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;</div><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00306"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">  306</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">SimpleTensor&lt;T&gt;::fixed_point_position</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;    <span class="keywordflow">return</span> _fixed_point_position;</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;}</div><div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00312"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">  312</a></span>&#160;<a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">SimpleTensor&lt;T&gt;::quantization_info</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;    <span class="keywordflow">return</span> _quantization_info;</div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;}</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00318"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">  318</a></span>&#160;<span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">SimpleTensor&lt;T&gt;::size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">size</a> = <a class="code" href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">std::accumulate</a>(_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a4498730adaf901d945c12841df994bba">cbegin</a>(), _shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#adf9b6d55d708c285d58511a780e937fc">cend</a>(), 1, std::multiplies&lt;size_t&gt;());</div><div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;    <span class="keywordflow">return</span> size * <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">element_size</a>();</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;}</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;</div><div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00325"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">  325</a></span>&#160;<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">SimpleTensor&lt;T&gt;::format</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;    <span class="keywordflow">return</span> _format;</div><div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;}</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00331"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">  331</a></span>&#160;<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">SimpleTensor&lt;T&gt;::data_layout</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;    <span class="keywordflow">return</span> _data_layout;</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;}</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00337"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">  337</a></span>&#160;<a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">SimpleTensor&lt;T&gt;::data_type</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;    <span class="keywordflow">if</span>(_format != <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">Format::UNKNOWN</a>)</div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    {</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;        <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a59846ef5ca75cd81cdb7e8a1ce08f9db">data_type_from_format</a>(_format);</div><div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;    }</div><div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;    {</div><div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;        <span class="keywordflow">return</span> _data_type;</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;    }</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;}</div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;</div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00350"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">  350</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">SimpleTensor&lt;T&gt;::num_channels</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;    <span class="keywordflow">switch</span>(_format)</div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    {</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">Format::U8</a>:</div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">Format::U16</a>:</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">Format::S16</a>:</div><div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">Format::U32</a>:</div><div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">Format::S32</a>:</div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">Format::F16</a>:</div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">Format::F32</a>:</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;            <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;        <span class="comment">// Because the U and V channels are subsampled</span></div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;        <span class="comment">// these formats appear like having only 2 channels:</span></div><div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a481e7a6945eb9f23e87f2de780b2e164">Format::YUYV422</a>:</div><div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58af557448a61ad2927194f63442e131dfa">Format::UYVY422</a>:</div><div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;            <span class="keywordflow">return</span> 2;</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a079eb95759d2ad31254f659d63651825">Format::UV88</a>:</div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;            <span class="keywordflow">return</span> 2;</div><div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">Format::RGB888</a>:</div><div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;            <span class="keywordflow">return</span> 3;</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a165f06116e7b8d9b2481dfc805db4619">Format::RGBA8888</a>:</div><div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;            <span class="keywordflow">return</span> 4;</div><div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">Format::UNKNOWN</a>:</div><div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;            <span class="keywordflow">return</span> _num_channels;</div><div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;        <span class="comment">//Doesn&#39;t make sense for planar formats:</span></div><div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a202f5d8c2c70d31048154d8b8b28e755">Format::NV12</a>:</div><div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a8e9f6aa1af7e0abbc7e64521e6ffe1b4">Format::NV21</a>:</div><div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ab08f0cb36474118c5bbc03b3a172a778">Format::IYUV</a>:</div><div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a11cfa56ee0ddbbc30a2fd189d7475f4c">Format::YUV444</a>:</div><div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;        <span class="keywordflow">default</span>:</div><div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;            <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;    }</div><div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;}</div><div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;</div><div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">  386</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">SimpleTensor&lt;T&gt;::num_elements</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;    <span class="keywordflow">return</span> _shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">total_size</a>();</div><div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;}</div><div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;</div><div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00392"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">  392</a></span>&#160;<a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">SimpleTensor&lt;T&gt;::padding</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;    <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a4467b302fc9ec312c40580336ab783da">PaddingSize</a>(0);</div><div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;}</div><div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;</div><div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00398"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">  398</a></span>&#160;<span class="keyword">const</span> T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">SimpleTensor&lt;T&gt;::data</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;    <span class="keywordflow">return</span> _buffer.get();</div><div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;}</div><div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;</div><div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00404"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#adc1e16b293a89a9ccc9541058b5ca560">  404</a></span>&#160;T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">SimpleTensor&lt;T&gt;::data</a>()</div><div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;{</div><div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;    <span class="keywordflow">return</span> _buffer.get();</div><div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;}</div><div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;</div><div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00410"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">  410</a></span>&#160;<span class="keyword">const</span> <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">SimpleTensor&lt;T&gt;::operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;coord)<span class="keyword"> const</span></div><div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;    <span class="keywordflow">return</span> _buffer.get() + <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(_shape, coord) * _num_channels;</div><div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;}</div><div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;</div><div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00416"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a2df95f7046b81e69a1265a42202ea068">  416</a></span>&#160;<span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">SimpleTensor&lt;T&gt;::operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;coord)</div><div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;{</div><div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;    <span class="keywordflow">return</span> _buffer.get() + <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(_shape, coord) * _num_channels;</div><div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;}</div><div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;</div><div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> U&gt;</div><div class="line"><a name="l00422"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">  422</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;U&gt;</a> &amp;tensor1, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;U&gt;</a> &amp;tensor2)</div><div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;{</div><div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;    <span class="comment">// Use unqualified call to swap to enable ADL. But make std::swap available</span></div><div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;    <span class="comment">// as backup.</span></div><div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;    <span class="keyword">using</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">std::swap</a>;</div><div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._shape, tensor2._shape);</div><div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._format, tensor2._format);</div><div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._data_type, tensor2._data_type);</div><div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._num_channels, tensor2._num_channels);</div><div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._fixed_point_position, tensor2._fixed_point_position);</div><div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._quantization_info, tensor2._quantization_info);</div><div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;    <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._buffer, tensor2._buffer);</div><div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;}</div><div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* __ARM_COMPUTE_TEST_SIMPLE_TENSOR_H__ */</span><span class="preprocessor"></span></div><div class="ttc" id="_i_accessor_8h_xhtml"><div class="ttname"><a href="_i_accessor_8h.xhtml">IAccessor.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a51920d34b0fa5415e84891ad8e755224"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">arm_compute::test::SimpleTensor::swap</a></div><div class="ttdeci">friend void swap(SimpleTensor&lt; U &gt; &amp;tensor1, SimpleTensor&lt; U &gt; &amp;tensor2)</div><div class="ttdoc">Swaps the content of the provided tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00422">SimpleTensor.h:422</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a4498730adaf901d945c12841df994bba"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a4498730adaf901d945c12841df994bba">arm_compute::Dimensions::cbegin</a></div><div class="ttdeci">std::array&lt; T, num_max_dimensions &gt;::const_iterator cbegin() const </div><div class="ttdoc">Returns a read-only (constant) iterator that points to the first element in the dimension array...</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00189">Dimensions.h:189</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58af557448a61ad2927194f63442e131dfa"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58af557448a61ad2927194f63442e131dfa">arm_compute::Format::UYVY422</a></div><div class="ttdoc">A single plane of 32-bit macro pixel of U0, Y0, V0, Y1 byte. </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a62b67b578f684c4d516843c9dea86a23"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">arm_compute::test::SimpleTensor::element_size</a></div><div class="ttdeci">size_t element_size() const override</div><div class="ttdoc">Size of each element in the tensor in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00300">SimpleTensor.h:300</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">arm_compute::test::RawTensor</a></div><div class="ttdoc">Subclass of SimpleTensor using uint8_t as value type. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00038">RawTensor.h:38</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ad7701a09a964eab360a8e51fa7ad2c16"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">arm_compute::test::SimpleTensor::size</a></div><div class="ttdeci">size_t size() const override</div><div class="ttdoc">Total size of the tensor in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00318">SimpleTensor.h:318</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_af6124c81d1e81f182d64ae76caa3fa52"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">arm_compute::test::SimpleTensor::operator[]</a></div><div class="ttdeci">T &amp; operator[](size_t offset)</div><div class="ttdoc">Return value at offset in the buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00282">SimpleTensor.h:282</a></div></div>
<div class="ttc" id="structarm__compute_1_1_border_size_xhtml"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml">arm_compute::BorderSize</a></div><div class="ttdoc">Container for 2D border size. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00291">Types.h:291</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">1 channel, 1 U8 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a34b06c0cd94808a77b697e79880b84b0"><div class="ttname"><a href="namespacearm__compute.xhtml#a34b06c0cd94808a77b697e79880b84b0">arm_compute::element_size_from_data_type</a></div><div class="ttdeci">size_t element_size_from_data_type(DataType dt)</div><div class="ttdoc">The size in bytes of the data type. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00182">Utils.h:182</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ac4b36cc1e56b0b7e579bb4b7196490db"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">arm_compute::test::SimpleTensor::format</a></div><div class="ttdeci">Format format() const override</div><div class="ttdoc">Image format of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00325">SimpleTensor.h:325</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a9a3e72153aeb3ed212e9c3698774e881"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">arm_compute::test::SimpleTensor::data_type</a></div><div class="ttdeci">DataType data_type() const override</div><div class="ttdoc">Data type of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00337">SimpleTensor.h:337</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a202f5d8c2c70d31048154d8b8b28e755"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a202f5d8c2c70d31048154d8b8b28e755">arm_compute::Format::NV12</a></div><div class="ttdoc">A 2 plane YUV format of Luma (Y) and interleaved UV data at 4:2:0 sampling. </div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a28edc8880596d14c099f3c2509efc8b3"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">arm_compute::test::swap</a></div><div class="ttdeci">void swap(SimpleTensor&lt; U &gt; &amp;tensor1, SimpleTensor&lt; U &gt; &amp;tensor2)</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00422">SimpleTensor.h:422</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 U16 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aba5871b3e4a65d057ec1c28fce8b00ba"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">arm_compute::test::SimpleTensor::shape</a></div><div class="ttdeci">TensorShape shape() const override</div><div class="ttdoc">Shape of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00294">SimpleTensor.h:294</a></div></div>
<div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00303">helpers.h:303</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a8e9f6aa1af7e0abbc7e64521e6ffe1b4"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a8e9f6aa1af7e0abbc7e64521e6ffe1b4">arm_compute::Format::NV21</a></div><div class="ttdoc">A 2 plane YUV format of Luma (Y) and interleaved VU data at 4:2:0 sampling. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a9be4cb7e6ee20063a4a10bc3abb750b9"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">arm_compute::test::coord2index</a></div><div class="ttdeci">int coord2index(const TensorShape &amp;shape, const Coordinates &amp;coord)</div><div class="ttdoc">Linearise the given coordinate. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00448">Utils.h:448</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::Format::RGB888</a></div><div class="ttdoc">3 channels, 1 U8 per channel </div></div>
<div class="ttc" id="arm__compute_2core_2_utils_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_utils_8h.xhtml">Utils.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_adf9b6d55d708c285d58511a780e937fc"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#adf9b6d55d708c285d58511a780e937fc">arm_compute::Dimensions::cend</a></div><div class="ttdeci">std::array&lt; T, num_max_dimensions &gt;::const_iterator cend() const </div><div class="ttdoc">Returns a read-only (constant) iterator that points one past the last element in the dimension array...</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00213">Dimensions.h:213</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a0c52a8f0085b55d907af7210ef2069d0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">arm_compute::test::SimpleTensor::data</a></div><div class="ttdeci">const T * data() const </div><div class="ttdoc">Constant pointer to the underlying buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00398">SimpleTensor.h:398</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 U32 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">arm_compute::Format</a></div><div class="ttdeci">Format</div><div class="ttdoc">Image colour formats. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00050">Types.h:50</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a16d7ecd97f89cf9dc40b3fc7c9abe2cd"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a16d7ecd97f89cf9dc40b3fc7c9abe2cd">arm_compute::test::SimpleTensor::~SimpleTensor</a></div><div class="ttdeci">~SimpleTensor()=default</div><div class="ttdoc">Default destructor. </div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item. </div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_afb9ded5f49336ae503bb9f2035ea902b"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b">arm_compute::test::SimpleTensor&lt; uint8_t &gt;::value_type</a></div><div class="ttdeci">uint8_t value_type</div><div class="ttdoc">Tensor value type. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00107">SimpleTensor.h:107</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a11cfa56ee0ddbbc30a2fd189d7475f4c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a11cfa56ee0ddbbc30a2fd189d7475f4c">arm_compute::Format::YUV444</a></div><div class="ttdoc">A 3 plane of 8 bit 4:4:4 sampled Y, U, V planes. </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a79e20eacb1e963e24a21ebd7369effd7"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">arm_compute::test::SimpleTensor::padding</a></div><div class="ttdeci">PaddingSize padding() const override</div><div class="ttdoc">Available padding around the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00392">SimpleTensor.h:392</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a5f63b63606dbbbe54474e6e970a6738c"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">arm_compute::test::SimpleTensor::data_layout</a></div><div class="ttdeci">DataLayout data_layout() const override</div><div class="ttdoc">Data layout of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00331">SimpleTensor.h:331</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a4467b302fc9ec312c40580336ab783da"><div class="ttname"><a href="namespacearm__compute.xhtml#a4467b302fc9ec312c40580336ab783da">arm_compute::PaddingSize</a></div><div class="ttdeci">BorderSize PaddingSize</div><div class="ttdoc">Container for 2D padding size. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00378">Types.h:378</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 S16 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width. </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a011bb65bd16aaf66b8efb3929692b2ce"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">arm_compute::test::SimpleTensor::SimpleTensor</a></div><div class="ttdeci">SimpleTensor()=default</div><div class="ttdoc">Create an uninitialised tensor. </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a39537b09ccc3ce3d17922f4ef49a123f"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">arm_compute::test::SimpleTensor::operator()</a></div><div class="ttdeci">const void * operator()(const Coordinates &amp;coord) const override</div><div class="ttdoc">Read only access to the specified element. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00410">SimpleTensor.h:410</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a59846ef5ca75cd81cdb7e8a1ce08f9db"><div class="ttname"><a href="namespacearm__compute.xhtml#a59846ef5ca75cd81cdb7e8a1ce08f9db">arm_compute::data_type_from_format</a></div><div class="ttdeci">DataType data_type_from_format(Format format)</div><div class="ttdoc">Return the data type used by a given single-planar pixel format. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00213">Utils.h:213</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_acf18a24d1f21176e811e88cee2a70f1f"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">arm_compute::test::SimpleTensor&lt; uint8_t &gt;::Buffer</a></div><div class="ttdeci">std::unique_ptr&lt; value_type[]&gt; Buffer</div><div class="ttdoc">Tensor buffer pointer type. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00109">SimpleTensor.h:109</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ab08f0cb36474118c5bbc03b3a172a778"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ab08f0cb36474118c5bbc03b3a172a778">arm_compute::Format::IYUV</a></div><div class="ttdoc">A 3 plane of 8-bit 4:2:0 sampled Y, U, V planes. </div></div>
<div class="ttc" id="tests_2_utils_8h_xhtml"><div class="ttname"><a href="tests_2_utils_8h.xhtml">Utils.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_abdd3637f2bbde9d7d0cc0b7bbd8400bb"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">arm_compute::test::SimpleTensor::num_channels</a></div><div class="ttdeci">int num_channels() const override</div><div class="ttdoc">Number of channels of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00350">SimpleTensor.h:350</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a165f06116e7b8d9b2481dfc805db4619"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a165f06116e7b8d9b2481dfc805db4619">arm_compute::Format::RGBA8888</a></div><div class="ttdoc">4 channels, 1 U8 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ad4622eda610d53fb6852209f0213aeed"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed">arm_compute::test::SimpleTensor::operator=</a></div><div class="ttdeci">SimpleTensor &amp; operator=(SimpleTensor tensor)</div><div class="ttdoc">Create a deep copy of the given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00274">SimpleTensor.h:274</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3"><div class="ttname"><a href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">arm_compute::CLVersion::UNKNOWN</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_i_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_i_accessor.xhtml">arm_compute::test::IAccessor</a></div><div class="ttdoc">Common interface to provide information and access to tensor like structures. </div><div class="ttdef"><b>Definition:</b> <a href="_i_accessor_8h_source.xhtml#l00037">IAccessor.h:37</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a079eb95759d2ad31254f659d63651825"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a079eb95759d2ad31254f659d63651825">arm_compute::Format::UV88</a></div><div class="ttdoc">2 channel, 1 U8 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aedcfdd4c3b92fe0d63b5463c7ad1d21e"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">arm_compute::test::SimpleTensor::num_elements</a></div><div class="ttdeci">int num_elements() const override</div><div class="ttdoc">Number of elements of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00386">SimpleTensor.h:386</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a4eaec01ba2c12093db609d1034ad0bc1"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">arm_compute::TensorShape::total_size</a></div><div class="ttdeci">size_t total_size() const </div><div class="ttdoc">Collapses all dimensions to a single linear total size. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00157">TensorShape.h:157</a></div></div>
<div class="ttc" id="accumulate_8cl_xhtml_a00e540076dd545ad59ac7482f8cdf514"><div class="ttname"><a href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">accumulate</a></div><div class="ttdeci">__kernel void accumulate(__global uchar *input_ptr, uint input_stride_x, uint input_step_x, uint input_stride_y, uint input_step_y, uint input_offset_first_element_in_bytes, __global uchar *accu_ptr, uint accu_stride_x, uint accu_step_x, uint accu_stride_y, uint accu_step_y, uint accu_offset_first_element_in_bytes)</div><div class="ttdoc">This function accumulates an input image into output image. </div><div class="ttdef"><b>Definition:</b> <a href="accumulate_8cl_source.xhtml#l00041">accumulate.cl:41</a></div></div>
<div class="ttc" id="structarm__compute_1_1_quantization_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_quantization_info.xhtml">arm_compute::QuantizationInfo</a></div><div class="ttdoc">Quantization settings (used for QASYMM8 data type) </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00127">Types.h:127</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ac74736e3863207232a23b7181c1d0f44"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">arm_compute::test::SimpleTensor::quantization_info</a></div><div class="ttdeci">QuantizationInfo quantization_info() const override</div><div class="ttdoc">Quantization info in case of asymmetric quantized type. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00312">SimpleTensor.h:312</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a481e7a6945eb9f23e87f2de780b2e164"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a481e7a6945eb9f23e87f2de780b2e164">arm_compute::Format::YUYV422</a></div><div class="ttdoc">A single plane of 32-bit macro pixel of Y0, U0, Y1, V0 bytes. </div></div>
<div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00072">Types.h:72</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a35ccf2eb0c18a15feab2db98b307b78b"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a35ccf2eb0c18a15feab2db98b307b78b">arm_compute::test::SimpleTensor::fixed_point_position</a></div><div class="ttdeci">int fixed_point_position() const override</div><div class="ttdoc">Number of bits for the fractional part. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00306">SimpleTensor.h:306</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdoc">Supported tensor data layouts. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00110">Types.h:110</a></div></div>
<div class="ttc" id="_tensor_shape_8h_xhtml"><div class="ttname"><a href="_tensor_shape_8h.xhtml">TensorShape.h</a></div></div>
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